The present invention relates to a method for determining a corrected variance representative of the condition of reception of signals representative of symbols transferred by an emitter to a receiver through a communication channel.
In radio communication systems, the estimation of the radio communication channel response between the emitter and the receiver is an essential operation that is performed at the receiver in order to improve the reception quality of the data by, as example, enabling a coherent demodulation of the received signals.
Generally, the estimation of the radio communication channel response is pilot-aided in the sense that a pilot signal known by the receiver is transmitted by the emitter in order to allow the estimation, at the receiver, of the radio communication channel response between the emitter and the receiver.
One of the most reliable pilot-aided radio communication channel estimator is the Minimum Mean Square Error (MMSE) estimator, also known as Wiener channel estimator. A Wiener channel estimator consists of a linear filter of L coefficients derived according to the minimum mean square error criterion.
A Wiener channel estimator requires the knowledge of the received average signal to interference plus noise ratio (SNR) over pilots and of the channel auto-correlation function. In practice, neither the received average SNR nor the channel auto-correlation function are precisely known.
For the auto-correlation function, a theoretical channel model is generally assumed with parameters determined from the parameters of the system under study. As example, in OFDM system, the radio communication channel is assumed to have rectangular shaped power delay profile with a maximum delay τmax and a rectangular shaped Doppler power spectrum with a maximum Doppler frequency fD,max. The parameters τmax and fD,max should always be equal or larger than the worst channel conditions.
For the received average SNR, a fixed average signal to interference plus noise ratio value SNRw is generally used to determine the coefficients of the Wiener channel estimator. The fixed average value SNRw has to be equal or larger than the actual received average SNR in order to achieve sub-optimal but still robust channel estimation performance in comparison with an optimal Wiener channel estimator. An optimal Wiener channel estimator is a Wiener channel estimator that uses the actual received average SNR to determine the Wiener filter coefficients. An actual value is a value currently received. The fixed average value SNRw is generally taken greater than an expected received average SNR chosen in a way to ensure optimal performance in the case of favourable transmission conditions.
The performance of the estimation of the radio communication channel response depends then on the channel auto-correlation model and the fixed average value SNRw used.
The performance of the Wiener channel estimator depends on the actual average received level of interference plus noise over pilots and also on the ratio Rboost between pilot signal power to data signal power. The ratio Rboost, referred to as power boost, is known by the receiver.
The higher the actual average level of interference plus noise is, the lower the channel estimation performance is. The higher the ratio Rboost is, the higher the channel estimation performance is.
At the receiver side, some other techniques or operations require the knowledge of the average received level of interference plus noise affecting the data signal in order to improve the reception quality. Examples of these operations are channel equalization and Log Likelihood Ratios (LLR) calculation for soft-in and soft-out channel decoding. So, when the same average received level of interference plus noise affects pilot and data signals, the estimation of the average received level of interference plus noise over pilots becomes vital for the radio communication channel estimation and/or for the channel equalization and/or for the Log Likelihood Ratios calculation.
Furthermore, the average received level of interference plus noise of the signals representative of pilot symbols and/or data symbols is a good indicator of the transmission quality that can be used as an input for efficient resource allocation like scheduling and/or link adaptation like adaptive modulation and/or coding scheme and/or Hybrid-Automatic Repeat reQuest, etc. and/or radio resource management mechanisms like handover, power control, etc.
Thus, the estimation of the average received level of interference plus noise is also vital for resource allocation, link adaptation, and radio resource management mechanisms.
Moreover, if the receiver is able to estimate the variance of channel estimation errors, one can take this information into account to improve the performance of the channel estimation for example through adaptive power boost and also some other receiver algorithms like channel equalization, Log Likelihood Ratios calculation and Channel Quality Indicator estimation.